Full scholarship PhD students are invited to apply to McGill University, Canada, for autumn 2024.

Scholarship: Fully funded
Degree: B.S./M.S.
Nationality: International Students
Location: Canada
Application deadlines: Open

Scholarship Description:

Founded in 1821, McGill University is Canada’s first university, located in Montreal, Quebec, Canada, and has produced 14 Nobel laureates, 144 Rhodes scholars, 8 heads of state, and 1 Turing Award winner. The school has long been ranked #1 among Canada’s research universities and #31 in the 2023 QS World University Rankings.The city of Montreal is friendly and welcoming, ranking 14th globally and 2nd in North America in the 2023 World’s Best Cities to Study in.Montreal’s direction in artificial intelligence has developed rapidly in recent years. Currently, Google (Google DeepMind, Google Brain), Facebook (Facebook Fair), Microsoft Research, Samsung (Samsung AI Research) and other technology giants have opened AI research centres in Montreal.

The Intelligent Automation Lab (http://mcgillialab.com/) in the Department of Computer Engineering at McGill University is directed by Professor Benoit Boulet (Vice-President of McGill University and MILA Board Director). The lab specialises in algorithms for intelligent decision making and their applications. Currently, the main research areas are: reinforcement learning, transfer learning, meta-learning, large model optimisation and applications, model predictive control; the main application areas are: smart grid, smart transportation, smart manufacturing, etc. The lab has undertaken more than 10 research projects over the years. Over the years, the lab has undertaken more than 13 million Canadian dollars in research projects and has close collaborations with ABB, AddEnergy, Quebec Power Authority and other companies. The lab provides each student with a good research hardware environment (RTX4080 or better, dual 4k monitor).

 Available Subjects:

  • Industrial applications of large language models (e.g. transport systems)
  • Basic models for reinforcement learning (focusing on safety, sample efficiency and generalisation)
  • AI/RL for energy
  • Time series forecasting in non-stationary environments

Eligibility criteria:

  • Applicants are expected to have a strong background in machine learning algorithms and programming skills.

Application Procedure:

You are welcome to contact us by email at [email protected] and cc [email protected]. Please include a CV, transcripts, and language scores.